期刊
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
卷 46, 期 7, 页码 1478-1484出版社
SPRINGER
DOI: 10.1007/s00259-019-04306-7
关键词
F-18-fluorodeoxyglucose positron emission tomography; magnetic resonance imaging; Oesophageal cancer; Radiomic analysis
资金
- Guys and St Thomas' Charity (Transforming Outcomes and Health Economics Project)
- King's College London / University College London Comprehensive Cancer Imaging Centres by Cancer Research UK
- King's College London / University College London Comprehensive Cancer Imaging Centres by Engineering and Physical Sciences Research Council
- Medical Research Council
- Department of Health [C1519/A16463]
- Wellcome Trust EPSRC Centre for Medical Engineering at King's College London [WT203148/Z/16/Z]
PurposeThe purpose of this study was to determine if F-18-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (F-18-FDG PET/MRI) features are associated with contemporaneous metastases in patients with oesophageal/gastroesophageal cancer.MethodsFollowing IRB approval and informed consent, patients underwent a staging PET/MRI following F-18-FDG injection (32628MBq) and 15623min uptake time. First-order histogram and second-order grey level co-occurrence matrix features were computed for PET standardized uptake value (SUV) and MRI T1-W, T2-W, diffusion weighted (DWI) and apparent diffusion coefficient (ADC) images for the whole tumour volume. K-means clustering assessed the correlation of feature-pairs with metastases. Multivariate analysis of variance (MANOVA) was performed to assess the statistical separability of the groups identified by feature-pairs. Sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), and accuracy (ACC) were calculated for these features and compared with SUVmax, ADC(mean) and maximum diameter alone for predicting contemporaneous metastases.Results Twenty patients (18 males, 2 female; median 67years, range 52-86) comprised the final study cohort; ten patients had metastases. Lower second-order SUV entropy combined with higher second-order ADC entropy were the best feature-pair for discriminating metastatic patients, MANOVA p value <0.001 (SN=80%, SP=80%, PPV=80%, NPV=80%, ACC=80%). SUVmax (SN=30%, SP=80%, PPV=60%, NPV=53%, ACC=55%), ADC(mean) (SN=20%, SP=70%, PPV=40%, NPV=47%, ACC=45%) and tumour maximum diameter (SN=10%, SP=90%, PPV=50%, NPV=50%, ACC=50%) had poorer sensitivity and accuracy.Conclusion High ADC entropy combined with low SUV entropy is associated with a higher prevalence of metastases and a promising initial signature for future study.
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